Projector-based augmented stacking framework for irregularly shaped objects

Abstract

Augmented reality in additive fabrication is predominantly applied to the manufacturing of structures from regularly shaped materials. Our work however embraces natural heterogeneity, by focusing on the assembly of irregularly shaped elements such as mineral scraps. We introduce a computer-aided framework with a 3D stacking engine and an augmented reality interface capable of guiding users through the balanced positioning of discrete and highly nonuniform objects according to an on-the-fly computed model and without prior trimming of the building unit. The pipeline is tested by the construction of two dry-stone structures (i.e., lacking any adhesives), and its accuracy is validated with a comparative study between the point cloud of the as-built digitized artifacts and the generated execution model, which shows an average 2.9 ± 1.8 cm error between the stones of the two models. We finally show how the proposed framework could be improved both in terms of software and hardware. In the interests of reproducibility, all the methods are shared as open source with the community. Graphical abstract

A framework for robotic excavation and dry stone construction using on-site materials

“…Because the machining of stone introduces additional process complexity and can substantially increase the carbon footprint of masonry construction (30), there is motivation to develop methods that can autonomously plan structures using entirely unmodified stone. Previous work in this domain has used simulated annealing to search for stone poses in a 2D scene (31) or a combination of physics simulation and heuristics to find stone poses for AR-assisted (32)(33)(34) or robotic (35) assembly. Furrer et al (36) used gradient descent and a support polygon-based cost function to create stacked towers of up to four stones, whereas Liu et al (35) achieved stacks up to six stones, and single-layer walls up to four courses, with a combination of hierarchical heuristics adapted from dry stone masonry guidebooks: Both studies built physical structures at the desktop scale in an open loop using prescanned stones that were localized for grasping with a manipulatormounted RGB-D sensor.…”

“…Because the machining of stone introduces additional process complexity and can substantially increase the carbon footprint of masonry construction ( 30 ), there is motivation to develop methods that can autonomously plan structures using entirely unmodified stone. Previous work in this domain has used simulated annealing to search for stone poses in a 2D scene ( 31 ) or a combination of physics simulation and heuristics to find stone poses for AR-assisted ( 32 – 34 ) or robotic ( 35 ) assembly. Furrer et al.…”